一种用于室外移动机器人的快速有效的车道线识别方法
A Fast and Efficient Lane Recognition Method for Outdoor Mobile Robots
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摘要: 提出了一种可满足室外移动机器人高速行驶要求的车道线检测识别方法.首先,对原始图像进行边缘抽取和动态双阈值二值化以得到二值化图像,再利用基于增强型状态转移网络(ATN)的图像理解算法识别出车道线.通过在清华大学室外移动机器人(THMR-V)平台上的大量试验证明了该算法的有效性和快速性.使用该算法的THMR-V(清华大学移动机器人-V)在高速公路上的最高自主行驶速度已经超过了150km/h.Abstract: This paper presents a lane recognition method which can satisfy the high-speed requirement of outdoor mobile robots.Firstly,we use edge extraction method and dynamic bi-threshold binarization algorithm to get a binary image from the original picture,then the ATN-based image comprehension method is used to get the position of lane.The method is used in THMR-V(TsingHua Mobile Robot-V) which also successfully achieves a maximal autonomous driving speed of 150km/h in highway.